REPOGEO REPORT · LITE
atfortes/Awesome-LLM-Reasoning
Default branch main · commit e01b133c · scanned 5/19/2026, 7:58:12 PM
GitHub: 3,616 stars · 206 forks
Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.
2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface atfortes/Awesome-LLM-Reasoning, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition README's opening to clarify its role as a research knowledge base
Why:
CURRENT<b> Curated collection of papers and resources on how to unlock the reasoning ability of LLMs and MLLMs.</b>
COPY-PASTE FIX<b> A comprehensive, curated collection of papers and resources designed for researchers and practitioners to deeply understand, explore, and advance the reasoning abilities of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs).</b>
- mediumhomepage#2Add a homepage URL to the repository's About section
Why:
COPY-PASTE FIXhttps://github.com/atfortes/Awesome-LLM-Reasoning
- lowtopics#3Add more specific research-oriented topics
Why:
CURRENTawesome, chain-of-thought, chatgpt, cot, deepseek, deepseek-r1, gpt, gpt-4o, in-context-learning, language-models, mllm, multimodal, openai-o1, papers, prompt, prompt-engineering, reasoning, strawberry
COPY-PASTE FIXawesome, chain-of-thought, chatgpt, cot, deepseek, deepseek-r1, gpt, gpt-4o, in-context-learning, language-models, llm-research, mllm, multimodal, openai-o1, papers, prompt, prompt-engineering, reasoning, research-papers, strawberry
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- LangChain · recommended 1×
- LlamaIndex · recommended 1×
- PaLM 2 · recommended 1×
- GPT-4 · recommended 1×
- Claude 2 · recommended 1×
- CATEGORY QUERYHow can I enhance the reasoning abilities of large language models for complex tasks?you: not recommendedAI recommended (in order):
- LangChain
- LlamaIndex
- PaLM 2
- GPT-4
- Claude 2
- Hugging Face Transformers
- OpenAI Fine-tuning API
- Pinecone
- Weaviate
- FAISS
- Wolfram Alpha API
- Prolog
- Auto-GPT
- BabyAGI
AI recommended 14 alternatives but never named atfortes/Awesome-LLM-Reasoning. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhat techniques exist to improve multimodal large language model reasoning through prompt engineering?you: not recommendedAI recommended (in order):
- GPT-4V (Vision)
- Gemini 1.5 Pro
- LLaVA (Large Language and Vision Assistant) (haotian-liu/LLaVA)
- Claude 3 Opus
- CogVLM (THUDM/CogVLM)
AI recommended 5 alternatives but never named atfortes/Awesome-LLM-Reasoning. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of atfortes/Awesome-LLM-Reasoning?passAI named atfortes/Awesome-LLM-Reasoning explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts atfortes/Awesome-LLM-Reasoning in production, what risks or prerequisites should they evaluate first?passAI named atfortes/Awesome-LLM-Reasoning explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo atfortes/Awesome-LLM-Reasoning solve, and who is the primary audience?passAI did not name atfortes/Awesome-LLM-Reasoning — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
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atfortes/Awesome-LLM-Reasoning — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite